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Religious Competition over Exorcism,ues that have been used for segmentation are minimum cost graph cuts and minimum cost paths. Methodology, parameterization, advantages, and problems for algorithms that are based on either of the two techniques are discussed in this chapter.

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https://doi.org/10.1007/978-981-16-5509-8variation of attributes within an object class while remaining suitably discriminative..Several techniques to generate and use object models will be presented in this chapter. Information about acceptable object variation in these models is either generated from training or it is part of the model prototype.

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Detection and Segmentation by Shape and Appearance,variation of attributes within an object class while remaining suitably discriminative..Several techniques to generate and use object models will be presented in this chapter. Information about acceptable object variation in these models is either generated from training or it is part of the model prototype.

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Classification and Clustering,ons are not estimated and the classification criterion is directly based on the training data..Feature reduction techniques, classifiers, and clustering methods that focus on analysis in sparse feature spaces are the topic of this chapter. These methods complement the methodology presented in Chap. ..

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Validation,ich the method is tested. These aspects are realized differently for a delineation task, a detection task, or a registration task. Requirements, means, and limitations of validation will be discussed in this chapter.